Statistics and Probability Commons^™

The Association Of Diet And Physical Activity With Stroke Mortality Results From The Adventist Health Study-1, Tahereh Zamansani

Loma Linda University Electronic Theses, Dissertations & Projects

Stroke is one of the leading causes of death and disability, with major global public health implications. Stroke ranks No. 4 among all causes of death, behind heart disease, cancer, and chronic lower respiratory disease (CLRD). Stroke accounts for almost 1 of every 18 deaths in the United States. Women accounted for 60.6% of stroke deaths. Death certificate data show that the mean age at stroke death was 79.6 years; males had a younger mean age (76.3) than females.

There is still a great scientific uncertainty among researchers and epidemiologists about the magnitude of any preventive effect, mechanisms of action …

Does The Sat Predict Academic Achievement And Academic Choices At Macalester College?, Jing Wen

Mathematics, Statistics, and Computer Science Honors Projects

This paper examines the predictive power of the Scholastic Aptitude Test (SAT) for Macalester students’ college success and academic choices. We use linear regression to study whether the SAT can predict students’ first year or four-year grades. Using Kullback-Leibler divergence and classification trees, we also examine the SAT’s predictive ability for other aspects of students’ academic experience, for example, major selection, or academic division of study. After controlling for major and course level, we find that the SAT does not explain a large proportion of the variability in Macalester students’ college success. However, the SAT does provide some useful information …

Enhancement Of Random Forests Using Trees With Oblique Splits, Andrejus Parfionovas

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Statistical classification is widely used in many areas where there is a need to make a data-driven decision, or to classify complicated cases or objects. For instance: disease diagnostics (is a patient sick or healthy, based on the blood test results?); weather forecasting (will there be a storm tomorrow, based on today's atmospheric pressure, air temperature, and wind velocity?); speech recognition (what was said over the phone, based on the caller's voice level and articulation); spam detection (can the unsolicited commercial e-mails be identified by their content?); and so on.

Classification trees …

Development Of Novel Methods To Minimize The Impact Of Sequencing Errors In The Next-Generation Sequencing Data Analysis, Xiaofeng Zheng

Dissertations and Theses (Open Access)

Next-generation sequencing (NGS) technology has become a prominent tool in biological and biomedical research. However, NGS data analysis, such as de novo assembly, mapping and variants detection is far from maturity, and the high sequencing error-rate is one of the major problems. .

To minimize the impact of sequencing errors, we developed a highly robust and efficient method, MTM, to correct the errors in NGS reads. We demonstrated the effectiveness of MTM on both single-cell data with highly non-uniform coverage and normal data with uniformly high coverage, reflecting that MTM’s performance does not rely on the coverage of the sequencing …

Integrative Biomarker Identification And Classification Using High Throughput Assays, Pan Tong

Dissertations and Theses (Open Access)

It is well accepted that tumorigenesis is a multi-step procedure involving aberrant functioning of genes regulating cell proliferation, differentiation, apoptosis, genome stability, angiogenesis and motility. To obtain a full understanding of tumorigenesis, it is necessary to collect information on all aspects of cell activity. Recent advances in high throughput technologies allow biologists to generate massive amounts of data, more than might have been imagined decades ago. These advances have made it possible to launch comprehensive projects such as (TCGA) and (ICGC) which systematically characterize the molecular fingerprints of cancer cells using gene expression, methylation, copy number, microRNA and SNP microarrays …

Level Crossing Times In Mathematical Finance, Ofosuhene Osei

Electronic Theses and Dissertations

Level crossing times and their applications in finance are of importance, given certain threshold levels that represent the "desirable" or "sell" values of a stock. In this thesis, we make use of Wald's lemmas and various deep results from renewal theory, in the context of finance, in modelling the growth of a portfolio of stocks. Several models are employed .

Existence And Multiplicity Results On Standing Wave Solutions Of Some Coupled Nonlinear Schrodinger Equations, Rushun Tian

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Coupled nonlinear Schrodinger equations (CNLS) govern many physical phenomena, such as nonlinear optics and Bose-Einstein condensates. For their wide applications, many studies have been carried out by physicists, mathematicians and engineers from different respects. In this dissertation, we focused on standing wave solutions, which are of particular interests for their relatively simple form and the important roles they play in studying other wave solutions. We studied the multiplicity of this type of solutions of CNLS via variational methods and bifurcation methods.

Variational methods are useful tools for studying differential equations and systems of differential equations that possess the so-called variational …

Statistical Algorithms For Optimal Experimental Design With Correlated Observations, Chang Li

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

The first part of my dissertation demonstrates that a modified simulated annealing algorithm can successfully determine highly efficient D-optimal designs for second order polynomial regression for a variety of correlated error structures.

In the second part, I solved weak universal optimal block designs for the nearest neighbor correlation structure and multiple block sizes, for the hub correlation structure with any block size, and for circulant correlation with odd block size.

In the third part, we propose an improved Particle Swarm Optimization (PSO) algorithm with time varying parameters. Then combining the theorem of decision making and PSO, we innovated nested PSO …

Spatially Indexed Functional Data, Oleksandr Gromenko

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

The increased concentration of greenhouse gases is associated with the global warming in the lower troposphere. For over twenty years, the space physics community has studied a hypothesis of global cooling in the thermosphere, attributable to greenhouse gases. While the global temperature increase in the lower troposphere has been relatively well established, the existence of global changes in the thermosphere is still under investigation.

A central difficulty in reaching definite conclusions is the absence of data with sufficiently long temporal and sufficiently broad spatial coverage. Time series of data that cover several decades exist only in a few separated (industrialized) …

Applications Of Bayesian Statistics In Fluvial Bed Load Transport, Mark L. Schmelter

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

The science of fluvial sediment transport studies the processes involved in the movement of river sediments. It is commonly understood that when rivers flood they have a great capacity to move sand, gravel, and even larger cobbles and boulders. This process is not only limited to the big floods that usually attract so much attention, but also the more common river flows play a very important role in forming a river. As engineers and scientists, we like to be able to develop equations and relationships that describe some natural phenomenon—in this case, fluvial sediment transport. While we are able to …

Empirical Properties Of Functional Regression Models And Application To High-Frequency Financial Data, Xi Zhang

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Functional data analysis (FDA) has grown into a substantial field of statistical research, with new methodology, numerous useful applications and interesting novel theoretical developments. My dissertation focuses on the empirical properties of functional regression models and their application to financial data. We start from testing the empirical properties of forecasts with the functional autoregressive models based on simulated and real data. We define intraday returns and consider their prediction from such returns on a market index. This is an extension to intraday data of the Capital Asset Pricing model. Finally we investigate multifactor functional models and assess their suitability for …

Probability Estimation In Random Forests, Chunyang Li

All Graduate Plan B and other Reports, Spring 1920 to Spring 2023

Random Forests is a useful ensemble approach that provides accurate predictions for classification, regression and many different machine learning problems. Classification has been a very useful and popular application for Random Forests. However, it is preferable to have the probability of a membership rather than the simple knowledge that one belongs to whichever group. Votes and the regression method are current probability estimation methods that have been developed in Random Forests. In this thesis, we introduce two new methods, proximity weighting and the out-of-bag method, trying to improve the current methods. Several different simulations are designed to evaluate the new …

Robust And Efficient Regression, Qi Zheng

All Dissertations

This dissertation aims to address two problems in regression
analysis. One problem is the model selection and robust parameter estimation in high dimensional linear regressions. The other is concerning developing a robust and efficient estimator in nonparametric regressions.
In Chapter 1, we introduce the robust and efficient regression analysis, discuss those two interesting problems and our motivations, and present several exciting results.
We propose a novel robust penalized method for high dimensional linear regression in Chapter 2. Asymptotic properties are established and a data-driven procedure is developed to select adaptive penalties. We show it is the very first estimator to …

Bayesian Hypothesis Testing And Variable Selection In High Dimensional Regression, Min Wang

All Dissertations

This dissertation consists of three distinct but related research projects. First of all, we study the Bayesian approach to model selection in the class of normal regression models. We propose an explicit closed-form expression of the Bayes factor with the use of Zellner's g-prior and the beta-prime prior for g. Noting that linear models with a growing number of unknown parameters have recently gained increasing popularity in practice, such as the spline problem, we shall thus be particularly interested in studying the model selection consistency of the Bayes factor under the scenario in which the dimension of the parameter space …

Structured Functional Principal Component Analysis, Haochang Shou, Vadim Zipunnikov, Ciprian Crainiceanu, Sonja Greven

Johns Hopkins University, Dept. of Biostatistics Working Papers

Motivated by modern observational studies, we introduce a class of functional models that expands nested and crossed designs. These models account for the natural inheritance of correlation structure from sampling design in studies where the fundamental sampling unit is a function or image. Inference is based on functional quadratics and their relationship with the underlying covariance structure of the latent processes. A computationally fast and scalable estimation procedure is developed for ultra-high dimensional data. Methods are illustrated in three examples: high-frequency accelerometer data for daily activity, pitch linguistic data for phonetic analysis, and EEG data for studying electrical brain activity …

Determinan Komplikasi Kronik Diabetes Melitus Pada Lanjut Usia, Amrina Rosyada, Indang Trihandini

Kesmas

Indonesia menghadapi jumlah penduduk lanjut usia (lansia) yang semakin meningkat dan diikuti oleh peningkatan frekuensi penyakit tidak menular kronis atau multimorbiditas. Penelitian ini bertujuan untuk mengetahui prevalensi dan faktor yang berhubungan komplikasi kronis pada lansia penderita diabetes melitus. Penelitian ini menggunakan data Riset Kesehatan Dasar (Riskesdas) Tahun 2007 dengan desain cross sectional representatif Indonesia dan metode cluster 2 tahap untuk pengambilan sampel. Sampel adalah 1.565 lansia penderita diabetes melitus. Metode analisis yang digunakan meliputi analisis deskriptif dan multivariat. Hasil analisis menunjukkan bahwa prevalensi komplikasi kronis pada lansia adalah sekitar 73,1%, dengan hipertensi sebagai komplikasi terbanyak. Berdasarkan analisis multivariat diketahui pula …

Choosing The Cut Point For A Restricted Mean In Survival Analysis, A Data Driven Method, Emily H. Sheldon

Theses and Dissertations

Survival Analysis generally uses the median survival time as a common summary statistic. While the median possesses the desirable characteristic of being unbiased, there are times when it is not the best statistic to describe the data at hand. Royston and Parmar (2011) provide an argument that the restricted mean survival time should be the summary statistic used when the proportional hazards assumption is in doubt. Work in Restricted Means dates back to 1949 when J.O. Irwin developed a calculation for the standard error of the restricted mean using Greenwood’s formula. Since then the development of the restricted mean has …

The Untenability Of A Priori Prior Probabilities In Objective Bayesian Conditionalization, C.S. Arledge

Senior Honors Theses

The problem of theory confirmation has been an issue in the philosophy of science for decades. Many valiant attempts have been made to formulate a generally accepted criterion for determining the validity of a scientific theory. Bayesian probability theory has been utilized in numerous attempts to examine the epistemic nature of theory confirmation and Jonathan Weisberg offers a formulation of Bayesian Conditionalization that he believes to be both objective and successful.

In this paper I intend to show the defects in Weisberg’s theory of objective Bayesian confirmation by utilizing the arguments of both W.V. Quine and Bas van Fraassen to …

Detecting And Correcting Batch Effects In High-Throughput Genomic Experiments, Sarah Reese

Theses and Dissertations

Batch effects are due to probe-specific systematic variation between groups of samples (batches) resulting from experimental features that are not of biological interest. Principal components analysis (PCA) is commonly used as a visual tool to determine whether batch effects exist after applying a global normalization method. However, PCA yields linear combinations of the variables that contribute maximum variance and thus will not necessarily detect batch effects if they are not the largest source of variability in the data. We present an extension of principal components analysis to quantify the existence of batch effects, called guided PCA (gPCA). We describe a …

Assessment Of Tillage Practices Using Landsat-Tm 5 In Nebraska., Sonisa Sharma

School of Natural Resources: Dissertations, Theses, and Student Research

Tillage management practices are an important component to crop production and to federal and state conservation efforts and crop subsidy programs. Crop residue created by conservation tillage reduces soil erosion and reduce evaporation from exposed soil. Agro-hydrological models require information on tillage practices to estimate their impacts on soil-water-holding capacity, total evapotranspiration, carbon sequestration, water runoff and water and wind erosion for agricultural lands. Classification of tillage practices using remote sensing offers promise for the rapid collection of tillage information on individual fields over large areas. Using satellite imagery proves to be challenging due to the similarity in spectral signatures …

Professor Salaries At Stephen F. Austin State University, Jami Miller

Undergraduate Research Conference

When I and my group mates started this project, we thought that professor salaries would average $70,000. We also thought that all the following would be significant and positive influences on salary: being male, a full time professor, having a doctorate, and the college taught in.

Economics And Attitude: The Effects Of Happiness On Economic Development, Chris Pace

Undergraduate Research Conference

No abstract provided.

Penalized Function-On-Function Regression, Andrada E. Ivanescu, Ana-Maria Staicu, Fabian Scheipl, Sonja Greven

Johns Hopkins University, Dept. of Biostatistics Working Papers

We propose a general framework for smooth regression of a functional response on one or multiple functional predictors. Using the mixed model representation of penalized regression expands the scope of function on function regression to many realistic scenarios. In particular, the approach can accommodate a densely or sparsely sampled functional response as well as multiple functional predictors that are observed: 1) on the same or different domains than the functional response; 2) on a dense or sparse grid; and 3) with or without noise. It also allows for seamless integration of continuous or categorical covariates and provides approximate confidence intervals …

Inflammatory Findings On Species Extrapolations: Humans Are Definitely No 70-Kg Mice, Marcel Leist, Thomas Hartung

Validation of Alternative Methods Collection

Modern toxicology has embraced in vitro methods, and major hopes are based on the Omics technologies and systems biology approaches they bring along (Hartung and McBride in ALTEX 28(2):83–93, 2011; Hartung et al. in ALTEX 29(2):119–28, 2012). A culture of stringent validation has been developed for such approaches (Leist et al. in ALTEX 27(4):309–317, 2010; ALTEX 29(4):373–88, 2012a; Toxicol Res 1:8–22, 2012b), while the quality and usefulness of animal experiments have been little scrutinized. A new study (Seok et al. 2013) now shows the low predictivity of animal responses in the field of inflammation. These findings corroborate earlier findings from …

Combinatorial Pooling Enables Selective Sequencing Of The Barley Gene Space, Stefano Lonardi, Denisa Duma, Matthew Alpert, Francesca Cordero, Marco Beccuti, Prasanna R. Bhat, Yonghui Wu, Gianfranco Ciardo, Burair Alsaihati, Steve Wanamaker, Josh Resnik, Serdar Bozdag, Ming-Cheng Luo, Timothy J. Close

Mathematics, Statistics and Computer Science Faculty Research and Publications

For the vast majority of species – including many economically or ecologically important organisms, progress in biological research is hampered due to the lack of a reference genome sequence. Despite recent advances in sequencing technologies, several factors still limit the availability of such a critical resource. At the same time, many research groups and international consortia have already produced BAC libraries and physical maps and now are in a position to proceed with the development of whole-genome sequences organized around a physical map anchored to a genetic map. We propose a BAC-by-BAC sequencing protocol that combines combinatorial pooling design and …

Direct Eit Reconstructions Of Complex Admittivities On A Chest-Shaped Domain In 2-D, Sarah J. Hamilton, Jennifer L. Mueller

Mathematics, Statistics and Computer Science Faculty Research and Publications

Electrical impedance tomography (EIT) is a medical imaging technique in which current is applied on electrodes on the surface of the body, the resulting voltage is measured, and an inverse problem is solved to recover the conductivity and/or permittivity in the interior. Images are then formed from the reconstructed conductivity and permittivity distributions. In the 2-D geometry, EIT is clinically useful for chest imaging. In this work, an implementation of a D-bar method for complex admittivities on a general 2-D domain is presented. In particular, reconstructions are computed on a chest-shaped domain for several realistic phantoms including a simulated pneumothorax, …

Customer Age As A Predictor Of Contact Volume, Tollan Renner

Honors Theses and Capstones

A two stage modeling approach for modeling customer age as a predictor of contact volume was conducted using a real-world data set of approximately 2,000,000 contacts from a company call center. Two models were constructed in the first stage, one a straightforward regression and the other a series of regressions. One was selected as better performing and scaled up to predict calls received from calls answered. The second stage of the modeling included a day of the week covariate and performed the best of the models created. This model uses age bins as model effects, of which the youngest age …

Age-Specific Signatures Of Glioblastoma At The Genomic, Genetic, And Epigenetic Levels, Serdar Bozdag, Aiguo Li, Gregory Riddick, Yuri Kotliarov, Mehmet Baysan, Fabio M. Iwamoto, Margaret C. Cam, Svetlana Kotliarova, Howard A. Fine

Mathematics, Statistics and Computer Science Faculty Research and Publications

Age is a powerful predictor of survival in glioblastoma multiforme (GBM) yet the biological basis for the difference in clinical outcome is mostly unknown. Discovering genes and pathways that would explain age-specific survival difference could generate opportunities for novel therapeutics for GBM. Here we have integrated gene expression, exon expression, microRNA expression, copy number alteration, SNP, whole exome sequence, and DNA methylation data sets of a cohort of GBM patients in The Cancer Genome Atlas (TCGA) project to discover age-specific signatures at the transcriptional, genetic, and epigenetic levels and validated our findings on the REMBRANDT data set. We found major …

Mathematical Modelling And Control Of Echinococcus In Qinghai Province, China, Liumei Wu, Baojun Song, Wen Du, Jie Lou

Department of Applied Mathematics and Statistics Faculty Scholarship and Creative Works

In this paper, two mathematical models, the baseline model and the intervention model, are proposed to study the transmission dynamics of echinococcus. A global forward bifurcation completely characterizes the dynamical behavior of the baseline model. That is, when the basic reproductive number is less than one, the disease-free equilibrium is asymptotically globally stable; when the number is greater than one, the endemic equilibrium is asymptotically globally stable. For the intervention model, however, the basic reproduction number alone is not enough to describe the dynamics, particularly for the case where the basic reproductive number is less then one. The emergence of …

Repeated Changes In Reported Sexual Orientation Identity Linked To Substance Use Behaviors In Youth, Miles Q. Ott, David Wypij, Heather L. Corliss, Margaret Rosario, Sari L. Reisner, Allegra R. Gordon, S. Bryn Austin

Statistical and Data Sciences: Faculty Publications

Purpose—Previous studies have found that sexual minority (e.g., lesbian, gay, bisexual) adolescents are at higher risk of substance use than heterosexuals, but few have examined how changes in sexual orientation over time may relate to substance use. We examined the associations between change in sexual orientation identity and marijuana use, tobacco use, and binge drinking in U.S. youth.

Methods—Prospective data from 10,515 U.S. youth ages 12-27 years in a longitudinal cohort study were analyzed using sexual orientation identity mobility measure M (frequency of change from 0 [no change] to 1 [change at every wave]) in up to five waves of …